Luxembourg Research Evaluation 2022: Field Mapping of Knowledge Structure

# Introduction:

Department

Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:

• To map the broader research community and distinct research field the department contributes to.
• Identify core knowledge bases, research areas gtrends and topics.
• Highlight the positioning of the department within this dynamics.

The method for the research-field-mapping can be reiviewed here:

Rakas, M., & Hain, D. S. (2019). The state of innovation system research: What happens beneath the surface?. Research Policy, 48(9), 103787.

Seed Articles

The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:

1. Via bibliographic clustering of the institutions publications and selection of most central articles per cluster (only clsuters where n >= 0.05N). Selection can be found at:https://github.com/daniel-hain/biblio_lux_2022/blob/master/output/seed/scopus_lih_tmoh_seed.csv
2. MAnual selection of relevant publications.
3. A combination of 1. and 2.

The present analysis is based on the following seed articles:

AU	PY	TI	JI
GONDER S;FERNANDEZ BOTANA I…	2020	METHOD FOR THE ANALYSIS OF THE TUMOR MICROENVIRONMENT BY MASS CYTOMETRY: APPLICATION TO CHRONIC L…	FRONT. IMMUNOL.
DITTMAR G;WINKLHOFER KF	2020	LINEAR UBIQUITIN CHAINS: CELLULAR FUNCTIONS AND STRATEGIES FOR DETECTION AND QUANTIFICATION	FRONT. CHEM.
SCHLICKER L;BOERS HM;DUDEK …	2019	POSTPRANDIALMETABOLIC EFFECTS OF FIBERMIXES REVEALED BY IN VIVO STABLE ISOTOPE LABELING IN HUMANS	METABOLITES
DUFRESNE J;BOWDEN P;THAVARA…	2018	THE PLASMA PEPTIDOME 03 CHEMICAL SCIENCES 0301 ANALYTICAL CHEMISTRY	CLIN. PROTEOMICS
BAHLAWANE C;SCHMITZ M;LETEL…	2017	INSIGHTS INTO LIGAND STIMULATION EFFECTS ON GASTRO-INTESTINAL STROMAL TUMORS SIGNALLING	CELL. SIGNAL.

Topic modelling

Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.

Topics by topwords

Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_lih_tmoh.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.

Topics over time

Technical Description

LDA Topic Modelling

Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA) is an example of topic model and is used to classify text in a document to a particular topic.

LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.

LDAVis

LDAvis is a web-based interactive visualisation of topics estimated using LDA. It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.

The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.

The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.

The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.

Knowledge Bases: Co-Citation network analysis

Note: This analysis refers the co-citation analysis, where the cited references and not the original publications are the unit of analysis. See tab Technical descriptionfor additional explanations

Knowledge Bases summary

In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.

com	name	dgr_int	dgr
Knowledge Base 1: KB 1 (n = 2190, density =2.88)
1	KOMANDER D. RAPE M. THE UBIQUITIN CODE (2012)	7044	9075
1	SWATEK K.N. KOMANDER D. UBIQUITIN MODIFICATIONS (2016)	3968	4657
1	YAU R. RAPE M. THE INCREASING COMPLEXITY OF THE UBIQUITIN CODE (2016)	3669	4111
1	HERSHKO A. CIECHANOVER A. THE UBIQUITIN SYSTEM (1998)	3513	4543
1	MEYER H.J. RAPE M. ENHANCED PROTEIN DEGRADATION BY BRANCHED UBIQUITIN CHAINS (2014)	2729	2874
1	HUSNJAK K. DIKIC I. UBIQUITIN-BINDING PROTEINS: DECODERS OF UBIQUITIN-MEDIATED CELLULAR FUNCTIONS (2012)	2284	2755
1	MEVISSEN T.E.T. KOMANDER D. MECHANISMS OF DEUBIQUITINASE SPECIFICITY AND REGULATION (2017)	2213	2616
1	YE Y. RAPE M. BUILDING UBIQUITIN CHAINS: E2 ENZYMES AT WORK (2009)	1242	1327
1	DESHAIES R.J. JOAZEIRO C.A. RING DOMAIN E3 UBIQUITIN LIGASES (2009)	1167	1338
1	XU P. DUONG D.M. SEYFRIED N.T. CHENG D. XIE Y. ROBERT J. RUSH J. PENG J. QUANTITATIVE PROTEOMICS REVEALS THE FUNCTION OF UNCONVENTIONAL UBIQUITIN C…	1095	1130
Knowledge Base 2: KB 2 (n = 931, density =6.17)
2	BRUGGNER R.V. BODENMILLER B. DILL D.L. TIBSHIRANI R.J. NOLAN G.P. AUTOMATED IDENTIFICATION OF STRATIFYING SIGNATURES IN CELLULAR SUBPOPULATIONS (2014)	1498	1501
2	VAN DER MAATEN L. HINTON G. VISUALIZING DATA USING T-SNE (2008)	1159	1165
2	WEBER L.M. ROBINSON M.D. COMPARISON OF CLUSTERING METHODS FOR HIGH-DIMENSIONAL SINGLE-CELL FLOW AND MASS CYTOMETRY DATA (2016)	1093	1093
2	SPITZER M.H. NOLAN G.P. MASS CYTOMETRY: SINGLE CELLS MANY FEATURES (2016)	1036	1036
2	LEVINE J.H. DATA-DRIVEN PHENOTYPIC DISSECTION OF AML REVEALS PROGENITOR-LIKE CELLS THAT CORRELATE WITH PROGNOSIS (2015)	951	951
2	SAMUSIK N. GOOD Z. SPITZER M.H. DAVIS K.L. NOLAN G.P. AUTOMATED MAPPING OF PHENOTYPE SPACE WITH SINGLE-CELL DATA (2016)	889	893
2	BENDALL S.C. NOLAN G.P. ROEDERER M. CHATTOPADHYAY P.K. A DEEP PROFILER’S GUIDE TO CYTOMETRY (2012)	766	766
2	BANDURA D.R. BARANOV V.I. ORNATSKY O.I. ANTONOV A. KINACH R. LOU X. PAVLOV S. TANNER S.D. MASS CYTOMETRY: TECHNIQUE FOR REAL TIME SINGLE CELL MULTI…	748	748
2	SHEKHAR K. BRODIN P. DAVIS M.M. CHAKRABORTY A.K. AUTOMATIC CLASSIFICATION OF CELLULAR EXPRESSION BY NONLINEAR STOCHASTIC EMBEDDING (ACCENSE)	703	703
2	KOTECHA N. KRUTZIK P.O. IRISH J.M. WEB-BASED ANALYSIS AND PUBLICATION OF FLOW CYTOMETRY EXPERIMENTS (2010)	680	683
Knowledge Base 3: KB 3 (n = 782, density =11.38)
3	MICHEAU O. TSCHOPP J. INDUCTION OF TNF RECEPTOR I-MEDIATED APOPTOSIS VIA TWO SEQUENTIAL SIGNALING COMPLEXES (2003)	1658	3414
3	HAAS T.L. EMMERICH C.H. GERLACH B. SCHMUKLE A.C. CORDIER S.M. RIESER E. FELTHAM R. WENGER T. RECRUITMENT OF THE LINEAR UBIQUITIN CHAIN ASSEMBLY COM…	1224	1379
3	KIRISAKO T. KAMEI K. MURATA S. KATO M. FUKUMOTO H. KANIE M. SANO S. IWAI K. A UBIQUITIN LIGASE COMPLEX ASSEMBLES LINEAR POLYUBIQUITIN CHAINS (2006)	1211	1713
3	DRABER P. KUPKA S. REICHERT M. DRABEROVA H. LAFONT E. DE MIGUEL D. SPILGIES L. HARTWIG T. LUBAC-RECRUITED CYLD AND A20 REGULATE GENE ACTIVATION AND…	1034	1123
3	GERLACH B. CORDIER S.M. SCHMUKLE A.C. EMMERICH C.H. RIESER E. HAAS T.L. WEBB A.I. WONG W.W. LINEAR UBIQUITINATION PREVENTS INFLAMMATION AND REGULAT…	973	1079
3	HE S. WANG L. MIAO L. WANG T. DU F. ZHAO L. WANG X. RECEPTOR INTERACTING PROTEIN KINASE-3 DETERMINES CELLULAR NECROTIC RESPONSE TO TNF-ALPHA (2009)	959	989
3	BERTRAND M.J. MILUTINOVIC S. DICKSON K.M. HO W.C. BOUDREAULT A. DURKIN J. GILLARD J.W. BARKER P.A. CIAP1 AND CIAP2 FACILITATE CANCER CELL SURVIVAL …	958	999
3	WANG L. DU F. WANG X. TNF-ALPHA INDUCES TWO DISTINCT CASPASE-8 ACTIVATION PATHWAYS (2008)	871	1500
3	OBERST A. DILLON C.P. WEINLICH R. MCCORMICK L.L. FITZGERALD P. POP C. HAKEM R. GREEN D.R. CATALYTIC ACTIVITY OF THE CASPASE-8-FLIP(L)	811	834
3	PELTZER N. RIESER E. TARABORRELLI L. DRABER P. DARDING M. PERNAUTE B. SHIMIZU Y. MONTINARO A. HOIP DEFICIENCY CAUSES EMBRYONIC LETHALITY BY ABERRAN…	742	779
Knowledge Base 4: KB 4 (n = 641, density =12.89)
4	MIETTINEN M. LASOTA J. GASTROINTESTINAL STROMAL TUMORS: PATHOLOGY AND PROGNOSIS AT DIFFERENT SITES (2006)	1351	1351
4	HIROTA S. ISOZAKI K. MORIYAMA Y. GAIN-OF-FUNCTION MUTATIONS OF C-KIT IN HUMAN GASTROINTESTINAL STROMAL TUMORS (1998)	1285	1285
4	VERWEIJ J. CASALI P.G. ZALCBERG J. PROGRESSION-FREE SURVIVAL IN GASTROINTESTINAL STROMAL TUMOURS WITH HIGH-DOSE IMATINIB: RANDOMISED TRIAL (2004)	1116	1116
4	HEINRICH M.C. CORLESS C.L. DUENSING A. PDGFRA ACTIVATING MUTATIONS IN GASTROINTESTINAL STROMAL TUMORS (2003)	1070	1070
4	DEMETRI G.D. VON MEHREN M. BLANKE C.D. EFFICACY AND SAFETY OF IMATINIB MESYLATE IN ADVANCED GASTROINTESTINAL STROMAL TUMORS (2002)	1053	1053
4	DEMETRI G.D. VAN OOSTEROM A.T. GARRETT C.R. EFFICACY AND SAFETY OF SUNITINIB IN PATIENTS WITH ADVANCED GASTROINTESTINAL STROMAL TUMOUR AFTER FAILUR…	907	907
4	BLANKE C.D. RANKIN C. DEMETRI G.D. PHASE III RANDOMIZED INTERGROUP TRIAL ASSESSING IMATINIB MESYLATE AT TWO DOSE LEVELS IN PATIENTS WITH UNRESECTAB…	806	806
4	HEINRICH M.C. CORLESS C.L. DEMETRI G.D. KINASE MUTATIONS AND IMATINIB RESPONSE IN PATIENTS WITH METASTATIC GASTROINTESTINAL STROMAL TUMOR (2003)	739	739
4	JOENSUU H. RISK STRATIFICATION OF PATIENTS DIAGNOSED WITH GASTROINTESTINAL STROMAL TUMOR (2008)	723	723
4	HEINRICH M.C. MAKI R.G. CORLESS C.L. PRIMARY AND SECONDARY KINASE GENOTYPES CORRELATE WITH THE BIOLOGICAL AND CLINICAL ACTIVITY OF SUNITINIB IN IMA…	721	721
Knowledge Base 5: KB 5 (n = 485, density =20.51)
5	GERLACH B. CORDIER S.M. SCHMUKLE A.C. EMMERICH C.H. RIESER E. HAAS T.L. LINEAR UBIQUITINATION PREVENTS INFLAMMATION AND REGULATES IMMUNE SIGNALLING…	1414	1727
5	HAAS T.L. EMMERICH C.H. GERLACH B. SCHMUKLE A.C. CORDIER S.M. RIESER E. RECRUITMENT OF THE LINEAR UBIQUITIN CHAIN ASSEMBLY COMPLEX STABILIZES THE T…	1110	1326
5	BOISSON B. LAPLANTINE E. DOBBS K. COBAT A. TARANTINO N. HAZEN M. HUMAN HOIP AND LUBAC DEFICIENCY UNDERLIES AUTOINFLAMMATION IMMUNODEFICIENCY AMYLOP…	931	1069
5	DRABER P. KUPKA S. REICHERT M. DRABEROVA H. LAFONT E. DE MIGUEL D. LUBAC-RECRUITED CYLD AND A20 REGULATE GENE ACTIVATION AND CELL DEATH BY EXERTING…	893	1062
5	BOISSON B. LAPLANTINE E. PRANDO C. GILIANI S. ISRAELSSON E. XU Z. IMMUNODEFICIENCY AUTOINFLAMMATION AND AMYLOPECTINOSIS IN HUMANS WITH INHERITED HO…	880	995
5	DAMGAARD R.B. WALKER J.A. MARCO-CASANOVA P. MORGAN N.V. TITHERADGE H.L. ELLIOTT P.R. THE DEUBIQUITINASE OTULIN IS AN ESSENTIAL NEGATIVE REGULATOR O…	846	991
5	ELLIOTT P.R. LESKE D. HRDINKA M. BAGOLA K. FIIL B.K. MCLAUGHLIN S.H. SPATA2 LINKS CYLD TO LUBAC ACTIVATES CYLD AND CONTROLS LUBAC SIGNALING (2016)	770	910
5	KEUSEKOTTEN K. ELLIOTT P.R. GLOCKNER L. FIIL B.K. DAMGAARD R.B. KULATHU Y. OTULIN ANTAGONIZES LUBAC SIGNALING BY SPECIFICALLY HYDROLYZING MET1-LINK…	694	961
5	FIIL B.K. DAMGAARD R.B. WAGNER S.A. KEUSEKOTTEN K. FRITSCH M. BEKKER-JENSEN S. OTULIN RESTRICTS MET1-LINKED UBIQUITINATION TO CONTROL INNATE IMMUNE…	683	811
5	KUPKA S. DE MIGUEL D. DRABER P. MARTINO L. SURINOVA S. RITTINGER K. SPATA2-MEDIATED BINDING OF CYLD TO HOIP ENABLES CYLD RECRUITMENT TO SIGNALING C…	682	820
Knowledge Base 6: KB 6 (n = 424, density =30.48)
6	GERLACH B. LINEAR UBIQUITINATION PREVENTS INFLAMMATION AND REGULATES IMMUNE SIGNALLING (2011)	1492	1741
6	HAAS T.L. RECRUITMENT OF THE LINEAR UBIQUITIN CHAIN ASSEMBLY COMPLEX STABILIZES THE TNF-R1 SIGNALING COMPLEX AND IS REQUIRED FOR TNF-MEDIATED GENE …	1213	1374
6	DRABER P. LUBAC-RECRUITED CYLD AND A20 REGULATE GENE ACTIVATION AND CELL DEATH BY EXERTING OPPOSING EFFECTS ON LINEAR UBIQUITIN IN SIGNALING COMPLE…	976	1075
6	DILLON C.P. RIPK1 BLOCKS EARLY POSTNATAL LETHALITY MEDIATED BY CASPASE-8 AND RIPK3 (2014)	879	914
6	JACO I. MK2 PHOSPHORYLATES RIPK1 TO PREVENT TNF-INDUCED CELL DEATH (2017)	837	902
6	SUN L. MIXED LINEAGE KINASE DOMAIN-LIKE PROTEIN MEDIATES NECROSIS SIGNALING DOWNSTREAM OF RIP3 KINASE (2012)	820	876
6	NEWTON K. RIPK3 DEFICIENCY OR CATALYTICALLY INACTIVE RIPK1 PROVIDES GREATER BENEFIT THAN MLKL DEFICIENCY IN MOUSE MODELS OF INFLAMMATION AND TISSUE…	768	799
6	PELTZER N. HOIP DEFICIENCY CAUSES EMBRYONIC LETHALITY BY ABERRANT TNFR1-MEDIATED ENDOTHELIAL CELL DEATH (2014)	765	848
6	BERGER S.B. CUTTING EDGE: RIP1 KINASE ACTIVITY IS DISPENSABLE FOR NORMAL DEVELOPMENT BUT IS A KEY REGULATOR OF INFLAMMATION IN SHARPIN-DEFICIENT MI…	736	770
6	DEGTEREV A. IDENTIFICATION OF RIP1 KINASE AS A SPECIFIC CELLULAR TARGET OF NECROSTATINS (2008)	711	745
Knowledge Base 7: KB 7 (n = 407, density =11.73)
7	CRAIG R. BEAVIS R.C. TANDEM: MATCHING PROTEINS WITH TANDEM MASS SPECTRA (2004)	1276	1276
7	COX J. MANN M. MAXQUANT ENABLES HIGH PEPTIDE IDENTIFICATION RATES INDIVIDUALIZED P.P.B.-RANGE MASS ACCURACIES AND PROTEOME-WIDE PROTEIN QUANTIFICAT…	705	1017
7	ENG J.K. MCCORMACK A.L. YATES J.R. AN APPROACH TO CORRELATE TANDEM MASS SPECTRAL DATA OF PEPTIDES WITH AMINO ACID SEQUENCES IN A PROTEIN DATABASE (…	427	446
7	ELIAS J.E. GYGI S.P. TARGET-DECOY SEARCH STRATEGY FOR INCREASED CONFIDENCE IN LARGE-SCALE PROTEIN IDENTIFICATIONS BY MASS SPECTROMETRY (2007)	353	380
7	BOWDEN P. BEAVIS R. MARSHALL J. TANDEM MASS SPECTROMETRY OF HUMAN TRYPTIC BLOOD PEPTIDES CALCULATED BY A STATISTICAL ALGORITHM AND CAPTURED BY A RE…	312	312
7	SCHWARTZ J.C. SENKO M.W. SYKA J.E. A TWO-DIMENSIONAL QUADRUPOLE ION TRAP MASS SPECTROMETER (2002)	304	304
7	ENG J.K. JAHAN T.A. HOOPMANN M.R. COMET: AN OPEN-SOURCE MS/MS SEQUENCE DATABASE SEARCH TOOL (2013)	295	295
7	BENJAMINI Y. HOCHBERG Y. CONTROLLING FALSE DISCOVERY RATE: A PRACTICAL APPROACH TO MULTIPLE TESTING (1995)	295	295
7	BOWDEN P. META SEQUENCE ANALYSIS OF HUMAN BLOOD PEPTIDES AND THEIR PARENT PROTEINS (2010)	294	294
7	BOWDEN P. QUANTITATIVE STATISTICAL ANALYSIS OF STANDARD AND HUMAN BLOOD PROTEINS FROM LIQUID CHROMATOGRAPHY ELECTROSPRAY IONIZATION AND TANDEM MASS…	294	294

Development of Knowledge Bases

Technical description

In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).

\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]

The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.

Research Areas: Bibliographic coupling analysis

Research Areas main summary

This is arguably the more interesting part. Here, we identify the literature’s current knowledge frontier by carrying out a bibliographic coupling analysis of the publications in our corpus. This measure uses bibliographical information of publications to establish a similarity relationship between them. Again, method details to be found in the tab Technical description. As you will see, we identify the main research area, but also a set of adjacent research areas with some theoretical/methodological/application overlap.

To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.

com_name	AU	PY	TI	dgr_int	TC	TC_year
Research Area 1: RA 1 (n = 765, density =0.32)
RA 1	SWATEK KN;KOMANDER D	2016	UBIQUITIN MODIFICATIONS	5.1272201	805	134.1666667
RA 1	YAU R;RAPE M	2016	THE INCREASING COMPLEXITY OF THE UBIQUITIN CODE	6.5307263	510	85.0000000
RA 1	MEVISSEN TET;KOMANDER D	2017	MECHANISMS OF DEUBIQUITINASE SPECIFICITY AND REGULATION	5.5094730	432	86.4000000
RA 1	KWON YT;CIECHANOVER A	2017	THE UBIQUITIN CODE IN THE UBIQUITIN-PROTEASOME SYSTEM AND AUTOPHAGY	6.5241986	312	62.4000000
RA 1	AKUTSU M;DIKIC I;BREMM A	2016	UBIQUITIN CHAIN DIVERSITY AT A GLANCE	7.2533119	257	42.8333333
RA 1	ZHENG N;SHABEK N	2017	UBIQUITIN LIGASES: STRUCTURE, FUNCTION, AND REGULATION	3.2312116	515	103.0000000
RA 1	BUETOW L;HUANG DT	2016	STRUCTURAL INSIGHTS INTO THE CATALYSIS AND REGULATION OF E3 UBIQUITIN LIGASES	6.1490412	252	42.0000000
RA 1	CLAGUE MJ;URBÉ S;KOMAN…	2019	BREAKING THE CHAINS: DEUBIQUITYLATING ENZYME SPECIFICITY BEGETS FUNCTION	5.3545038	253	84.3333333
RA 1	OHTAKE F;SAEKI Y;ISHID…	2016	THE K48-K63 BRANCHED UBIQUITIN CHAIN REGULATES NF-ΚB SIGNALING	8.2297279	155	25.8333333
RA 1	OHTAKE F;TSUCHIYA H;SA…	2018	K63 UBIQUITYLATION TRIGGERS PROTEASOMAL DEGRADATION BY SEEDING BRANCHED UBIQUITIN CHAINS	9.6846455	117	29.2500000
Research Area 2: RA 2 (n = 684, density =0.22)
RA 2	SPITZER MH;NOLAN GP	2016	MASS CYTOMETRY: SINGLE CELLS, MANY FEATURES	8.4260663	607	101.1666667
RA 2	BECHT E;MCINNES L;HEAL…	2019	DIMENSIONALITY REDUCTION FOR VISUALIZING SINGLE-CELL DATA USING UMAP	2.9448535	1214	404.6666667
RA 2	WOLF FA;ANGERER P;THEI…	2018	SCANPY: LARGE-SCALE SINGLE-CELL GENE EXPRESSION DATA ANALYSIS	2.2441145	1050	262.5000000
RA 2	CHEVRIER S;LEVINE JH;Z…	2017	AN IMMUNE ATLAS OF CLEAR CELL RENAL CELL CARCINOMA	3.1459785	485	97.0000000
RA 2	WEI SC;LEVINE JH;COGDI…	2017	DISTINCT CELLULAR MECHANISMS UNDERLIE ANTI-CTLA-4 AND ANTI-PD-1 CHECKPOINT BLOCKADE	2.2863878	643	128.6000000
RA 2	AZIZI E;CARR AJ;PLITAS…	2018	SINGLE-CELL MAP OF DIVERSE IMMUNE PHENOTYPES IN THE BREAST TUMOR MICROENVIRONMENT	1.7005383	653	163.2500000
RA 2	SAEYS Y;VAN GASSEN S;L…	2016	COMPUTATIONAL FLOW CYTOMETRY: HELPING TO MAKE SENSE OF HIGH-DIMENSIONAL IMMUNOLOGY DATA	3.9600564	252	42.0000000
RA 2	WAGNER J;RAPSOMANIKI M…	2019	A SINGLE-CELL ATLAS OF THE TUMOR AND IMMUNE ECOSYSTEM OF HUMAN BREAST CANCER	3.4354435	272	90.6666667
RA 2	SETTY M;TADMOR MD;REIC…	2016	WISHBONE IDENTIFIES BIFURCATING DEVELOPMENTAL TRAJECTORIES FROM SINGLE-CELL DATA	2.9063262	317	52.8333333
RA 2	HABER AL;BITON M;ROGEL…	2017	A SINGLE-CELL SURVEY OF THE SMALL INTESTINAL EPITHELIUM	1.3689450	603	120.6000000
Research Area 3: RA 3 (n = 499, density =0.26)
RA 3	SIDDIQUI I;SCHAEUBLE K…	2019	INTRATUMORAL TCF1 + PD-1 + CD8 + T CELLS WITH STEM-LIKE PROPERTIES PROMOTE TUMOR CONTROL IN RESPONSE TO VACCINATION AND CH…	1.9260532	435	145.0000000
RA 3	CASSETTA L;FRAGKOGIANN…	2019	HUMAN TUMOR-ASSOCIATED MACROPHAGE AND MONOCYTE TRANSCRIPTIONAL LANDSCAPES REVEAL CANCER-SPECIFIC REPROGRAMMING, BIOMARKERS…	1.3934573	313	104.3333333
RA 3	JIA D;LI S;LI D;XUE H;…	2018	MINING TCGA DATABASE FOR GENES OF PROGNOSTIC VALUE IN GLIOBLASTOMA MICROENVIRONMENT	2.0598796	186	46.5000000
RA 3	HUNDHAUSEN C;ROTH A;WH…	2016	ENHANCED T CELL RESPONSES TO IL-6 IN TYPE 1 DIABETES ARE ASSOCIATED WITH EARLY CLINICAL DISEASE AND INCREASED IL-6 RECEPTO…	3.5596426	57	9.5000000
RA 3	CHEN L;LU D;SUN K;XU Y…	2019	IDENTIFICATION OF BIOMARKERS ASSOCIATED WITH DIAGNOSIS AND PROGNOSIS OF COLORECTAL CANCER PATIENTS BASED ON INTEGRATED BIO…	3.4102884	58	19.3333333
RA 3	CHAUDHARY K;POIRION OB…	2018	DEEP LEARNING–BASED MULTI-OMICS INTEGRATION ROBUSTLY PREDICTS SURVIVAL IN LIVER CANCER	0.5616913	347	86.7500000
RA 3	MAN K;GABRIEL SS;LIAO …	2017	TRANSCRIPTION FACTOR IRF4 PROMOTES CD8+ T CELL EXHAUSTION AND LIMITS THE DEVELOPMENT OF MEMORY-LIKE T CELLS DURING CHRONIC…	1.1712076	166	33.2000000
RA 3	OMENETTI S;BUSSI C;MET…	2019	THE INTESTINE HARBORS FUNCTIONALLY DISTINCT HOMEOSTATIC TISSUE-RESIDENT AND INFLAMMATORY TH17 CELLS	1.3381012	106	35.3333333
RA 3	CHEN L;YUAN L;WANG Y;W…	2017	CO-EXPRESSION NETWORK ANALYSIS IDENTIFIED FCER1G IN ASSOCIATION WITH PROGRESSION AND PROGNOSIS IN HUMAN CLEAR CELL RENAL C…	1.9524960	71	14.2000000
RA 3	MEYER-SCHALLER N;CARDN…	2019	A HIERARCHICAL REGULATORY LANDSCAPE DURING THE MULTIPLE STAGES OF EMT	3.3852320	36	12.0000000
Research Area 4: RA 4 (n = 436, density =0.39)
RA 4	KALLIOLIAS GD;IVASHKIV LB	2016	TNF BIOLOGY, PATHOGENIC MECHANISMS AND EMERGING THERAPEUTIC STRATEGIES	1.6882166	564	94.0000000
RA 4	ZHANG Q;LENARDO MJ;BAL…	2017	30 YEARS OF NF-ΚB: A BLOSSOMING OF RELEVANCE TO HUMAN PATHOBIOLOGY	1.0405773	906	181.2000000
RA 4	LAFONT E;DRABER P;RIES…	2018	TBK1 AND IKKΕ PREVENT TNF-INDUCED CELL DEATH BY RIPK1 PHOSPHORYLATION	6.1194171	115	28.7500000
RA 4	JACO I;ANNIBALDI A;LAL…	2017	MK2 PHOSPHORYLATES RIPK1 TO PREVENT TNF-INDUCED CELL DEATH	4.4520368	158	31.6000000
RA 4	YUAN J;AMIN P;OFENGEIM D	2019	NECROPTOSIS AND RIPK1-MEDIATED NEUROINFLAMMATION IN CNS DISEASES	2.8333469	245	81.6666667
RA 4	AFONINA IS;ZHONG Z;KAR…	2017	LIMITING INFLAMMATION - THE NEGATIVE REGULATION OF NF-B AND THE NLRP3 INFLAMMASOME	2.0213319	324	64.8000000
RA 4	NEWTON K;DUGGER DL;MAL…	2016	RIPK3 DEFICIENCY OR CATALYTICALLY INACTIVE RIPK1 PROVIDES GREATER BENEFIT THAN MLKL DEFICIENCY IN MOUSE MODELS OF INFLAMMA…	2.4160591	260	43.3333333
RA 4	ANNIBALDI A;MEIER P	2018	CHECKPOINTS IN TNF-INDUCED CELL DEATH: IMPLICATIONS IN INFLAMMATION AND CANCER	4.6201760	114	28.5000000
RA 4	DAMGAARD RB;WALKER JA;…	2016	THE DEUBIQUITINASE OTULIN IS AN ESSENTIAL NEGATIVE REGULATOR OF INFLAMMATION AND AUTOIMMUNITY	3.0168380	174	29.0000000
RA 4	TING AT;BERTRAND MJM	2016	MORE TO LIFE THAN NF-ΚB IN TNFR1 SIGNALING	3.7053416	141	23.5000000
Research Area 5: RA 5 (n = 375, density =0.63)
RA 5	MEHREN MV;JOENSUU H	2018	GASTROINTESTINAL STROMAL TUMORS	9.8259758	129	32.2500000
RA 5	JOENSUU H;ERIKSSON M;S…	2016	ADJUVANT IMATINIB FOR HIGH-RISK GI STROMAL TUMOR: ANALYSIS OF A RANDOMIZED TRIAL	8.7968715	135	22.5000000
RA 5	JOENSUU H;WARDELMANN E…	2017	EFFECT OF KIT AND PDGFRA MUTATIONS ON SURVIVAL IN PATIENTS WITH GASTROINTESTINAL STROMAL TUMORS TREATED WITH ADJUVANT IMAT…	6.9814786	93	18.6000000
RA 5	NISHIDA T;BLAY J-Y;HIR…	2016	THE STANDARD DIAGNOSIS, TREATMENT, AND FOLLOW-UP OF GASTROINTESTINAL STROMAL TUMORS BASED ON GUIDELINES	2.5769039	209	34.8333333
RA 5	BLAY J-Y;SERRANO C;HEI…	2020	RIPRETINIB IN PATIENTS WITH ADVANCED GASTROINTESTINAL STROMAL TUMOURS (INVICTUS): A DOUBLE-BLIND, RANDOMISED, PLACEBO-CONT…	5.2016129	103	51.5000000
RA 5	CASALI PG;FUMAGALLI E;…	2017	TEN-YEAR PROGRESSION-FREE AND OVERALL SURVIVAL IN PATIENTS WITH UNRESECTABLE OR METASTATIC GI STROMAL TUMORS: LONG-TERM AN…	5.3497528	92	18.4000000
RA 5	RAUT CP;ESPAT NJ;MAKI …	2018	EFFICACY AND TOLERABILITY OF 5-YEAR ADJUVANT IMATINIB TREATMENT FOR PATIENTS WITH RESECTED INTERMEDIATE- OR HIGH-RISK PRIM…	9.0031630	50	12.5000000
RA 5	HEINRICH MC;JONES RL;V…	2020	AVAPRITINIB IN ADVANCED PDGFRA D842V-MUTANT GASTROINTESTINAL STROMAL TUMOUR (NAVIGATOR): A MULTICENTRE, OPEN-LABEL, PHASE …	4.5861442	90	45.0000000
RA 5	KOO D-H;RYU M-H;KIM K-…	2016	ASIAN CONSENSUS GUIDELINES FOR THE DIAGNOSIS AND MANAGEMENT OF GASTROINTESTINAL STROMAL TUMOR	4.5590811	90	15.0000000
RA 5	AKAHOSHI K;OYA M;KOGA …	2018	CURRENT CLINICAL MANAGEMENT OF GASTROINTESTINAL STROMAL TUMOR	4.0173370	98	24.5000000
Research Area 6: RA 6 (n = 343, density =0.36)
RA 6	PINO LK;SEARLE BC;BOLL…	2020	THE SKYLINE ECOSYSTEM: INFORMATICS FOR QUANTITATIVE MASS SPECTROMETRY PROTEOMICS	2.6170797	193	96.5000000
RA 6	THE M;MACCOSS MJ;NOBLE…	2016	FAST AND ACCURATE PROTEIN FALSE DISCOVERY RATES ON LARGE-SCALE PROTEOMICS DATA SETS WITH PERCOLATOR 3.0	3.6126290	130	21.6666667
RA 6	LANGELLA O;VALOT B;BAL…	2017	X!TANDEMPIPELINE: A TOOL TO MANAGE SEQUENCE REDUNDANCY FOR PROTEIN INFERENCE AND PHOSPHOSITE IDENTIFICATION	4.3603205	100	20.0000000
RA 6	GEYER PE;HOLDT LM;TEUP…	2017	REVISITING BIOMARKER DISCOVERY BY PLASMA PROTEOMICS	1.3686954	318	63.6000000
RA 6	GESSULAT S;SCHMIDT T;Z…	2019	PROSIT: PROTEOME-WIDE PREDICTION OF PEPTIDE TANDEM MASS SPECTRA BY DEEP LEARNING	1.1098241	224	74.6666667
RA 6	GEYER PE;WEWER ALBRECH…	2016	PROTEOMICS REVEALS THE EFFECTS OF SUSTAINED WEIGHT LOSS ON THE HUMAN PLASMA PROTEOME	1.5790183	118	19.6666667
RA 6	RANDLES MJ;HUMPHRIES M…	2017	PROTEOMIC DEFINITIONS OF BASEMENT MEMBRANE COMPOSITION IN HEALTH AND DISEASE	1.9849478	76	15.2000000
RA 6	WICHMANN C;MEIER F;WIN…	2019	MAXQUANT.LIVE ENABLES GLOBAL TARGETING OF MORE THAN 25,000 PEPTIDES	3.0851013	47	15.6666667
RA 6	SCHWENK JM;OMENN GS;SU…	2017	THE HUMAN PLASMA PROTEOME DRAFT OF 2017: BUILDING ON THE HUMAN PLASMA PEPTIDEATLAS FROM MASS SPECTROMETRY AND COMPLEMENTAR…	1.2358327	109	21.8000000
RA 6	TSOU C-C;TSAI C-F;TEO …	2016	UNTARGETED, SPECTRAL LIBRARY-FREE ANALYSIS OF DATA-INDEPENDENT ACQUISITION PROTEOMICS DATA GENERATED USING ORBITRAP MASS S…	2.9080684	46	7.6666667
Research Area 7: RA 7 (n = 302, density =3.08)
RA 7	HESTHAVEN JS;UBBIALI S	2018	NON-INTRUSIVE REDUCED ORDER MODELING OF NONLINEAR PROBLEMS USING NEURAL NETWORKS	7.8040049	154	38.5000000
RA 7	LIEVENS A;JACCHIA S;KA…	2016	MEASURING DIGITAL PCR QUALITY: PERFORMANCE PARAMETERS AND THEIR OPTIMIZATION	10.8998666	74	12.3333333
RA 7	BANGALORE P;LETZGUS S;…	2017	AN ARTIFICIAL NEURAL NETWORK-BASED CONDITION MONITORING METHOD FOR WIND TURBINES, WITH APPLICATION TO THE MONITORING OF TH…	9.5373716	79	15.8000000
RA 7	ASKHAM T;KUTZ JN	2018	VARIABLE PROJECTION METHODS FOR AN OPTIMIZED DYNAMIC MODE DECOMPOSITION	8.0648413	73	18.2500000
RA 7	LAZZARI F;BUFFI A;NEPA…	2017	NUMERICAL INVESTIGATION OF AN UWB LOCALIZATION TECHNIQUE FOR UNMANNED AERIAL VEHICLES IN OUTDOOR SCENARIOS	11.5838130	41	8.2000000
RA 7	LASSENBERGER A;GRÜNEWA…	2017	MONODISPERSE IRON OXIDE NANOPARTICLES BY THERMAL DECOMPOSITION: ELUCIDATING PARTICLE FORMATION BY SECOND-RESOLVED IN SITU …	7.7476544	60	12.0000000
RA 7	BARBIERI S;DONATI OF;F…	2016	IMPACT OF THE CALCULATION ALGORITHM ON BIEXPONENTIAL FITTING OF DIFFUSION-WEIGHTED MRI IN UPPER ABDOMINAL ORGANS	7.8235777	58	9.6666667
RA 7	ROBERT DJ;RAJEEV P;KOD…	2016	EQUATION TO PREDICT MAXIMUM PIPE STRESS INCORPORATING INTERNAL AND EXTERNAL LOADINGS ON BURIED PIPES	13.2664507	28	4.6666667
RA 7	AMIGO JM;DEL OLMO ALVA…	2016	STALING OF WHITE WHEAT BREAD CRUMB AND EFFECT OF MALTOGENIC Α-AMYLASES. PART 1: SPATIAL DISTRIBUTION AND KINETIC MODELING …	9.7564730	38	6.3333333
RA 7	ARSLAN D;CHONG KE;MIRO…	2017	ANGLE-SELECTIVE ALL-DIELECTRIC HUYGENS’ METASURFACES	9.4285586	39	7.8000000
Research Area 8: RA 8 (n = NA, density =NA)
NA	HIPP G;VAILLANT M;DIED…	2018	THE LUXEMBOURG PARKINSON’S STUDY: A COMPREHENSIVE APPROACH FOR STRATIFICATION AND EARLY DIAGNOSIS	0.0275229	25	6.2500000
NA	KRÄMER L;JÄGER C;TREZZ…	2018	QUANTIFICATION OF STABLE ISOTOPE TRACES CLOSE TO NATURAL ENRICHMENT IN HUMAN PLASMA METABOLITES USING GAS CHROMATOGRAPHY-M…	0.0714286	7	1.7500000
NA	SIMONS JA;VAILLANT M;H…	2019	MULTILINGUAL VALIDATION OF THE FIRST FRENCH VERSION OF MUNICH DYSPHAGIA TEST—PARKINSON’S DISEASE (MDT-PD) IN THE LUXEMBOUR…	0.0275229	1	0.3333333
NA	BOUR C;SCHMITZ S;AHNE …	2021	SCOPING REVIEW PROTOCOL ON THE USE OF SOCIAL MEDIA FOR HEALTH RESEARCH PURPOSES	0.0091743	2	2.0000000
NA	LINN N;GOETZINGER C;RE…	2021	DIGITAL HEALTH INTERVENTIONS AMONG PEOPLE LIVING WITH FRAILTY: A SCOPING REVIEW	0.0091743	1	1.0000000
NA	FAGHERAZZI G;ZHANG L;A…	2021	TOWARDS PRECISION CARDIOMETABOLIC PREVENTION: RESULTS FROM A MACHINE LEARNING, SEMI-SUPERVISED CLUSTERING APPROACH IN THE …	0.0000000	0	0.0000000
NA	ROSALES JUBAL E;SCHWAL…	2021	ACITRETIN REVERSES EARLY FUNCTIONAL NETWORK DEGRADATION IN A MOUSE MODEL OF FAMILIAL ALZHEIMER’S DISEASE	0.0000000	3	3.0000000
NA	LEONARD C;MONTAMAT G;D…	2021	COMPREHENSIVE MAPPING OF IMMUNE TOLERANCE YIELDS A REGULATORY TNF RECEPTOR 2 SIGNATURE IN A MURINE MODEL OF SUCCESSFUL FEL…	0.0000000	2	2.0000000
NA	BOUR C;AHNE A;SCHMITZ …	2021	THE USE OF SOCIAL MEDIA FOR HEALTH RESEARCH PURPOSES: SCOPING REVIEW	0.0000000	3	3.0000000
NA	ADAMS P;FIEVEZ V;SCHOB…	2021	CD32+CD4+ MEMORY T CELLS ARE ENRICHED FOR TOTAL HIV-1 DNA IN TISSUES FROM HUMANIZED MICE	0.0000000	3	3.0000000

Development

Connectivity between the research areas

Technical description

In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.

\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]

Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).

\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]

More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.

Knowledge Bases, Research Areas & Topics Interaction

Endnotes

All results are preliminary so far…